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Data:
1954 2302 3054 2414 2226 2725 2589 3470 2400 3180 4009 3924 2072 2434 2956 2828 2687 2629 3150 4119 3030 3055 3821 4001 2529 2472 3134 2789 2758 2993 3282 3437 2804 3076 3782 3889 2271 2452 3084 2522 2769 3438 2839 3746 2632 2851 3871 3618 2389 2344 2678 2492 2858 2246 2800 3869 3007 3023 3907 4209 2353 2570 2903 2910 3782 2759 2931 3641 2794 3070 3576 4106 2452 2206 2488 2416 2534 2521 3093 3903 2907 3025 3812 4209 2138 2419 2622 2912 2708 2798 3254 2895 3263 3736 4077 4097 2175 3138 2823 2498 2822 2738 4137 3515 3785 3632 4504 4451 2550 2867 3458 2961 3163 2880 3331 3062 3534 3622 4464 5411 2564 2820 3508 3088 3299 2939 3320 3418 3604 3495 4163 4882 2211 3260 2992 2425 2707 3244 3965 3315 3333 3583 4021 4904 2252 2952 3573 3048 3059 2731 3563 3092 3478 3478 4308 5029 2075 3264 3308 3688 3136 2824 3644 4694 2914 3686 4358 5587 2265 3685 3754 3708 3210 3517 3905


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highest quantile


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R Code
par1 <- as(par1,'numeric') par2 <- as(par2,'numeric') par3 <- as(par3,'numeric') library(Hmisc) myseq <- seq(par1, par2, par3) hd <- hdquantile(x, probs = myseq, se = TRUE, na.rm = FALSE, names = TRUE, weights=FALSE) bitmap(file='test1.png') plot(myseq,hd,col=2,main=main,xlab=xlab,ylab=ylab) grid() dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Harrell-Davis Quantiles',3,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'quantiles',header=TRUE) a<-table.element(a,'value',header=TRUE) a<-table.element(a,'standard error',header=TRUE) a<-table.row.end(a) length(hd) for (i in 1:length(hd)) { a<-table.row.start(a) a<-table.element(a,as(labels(hd)[i],'numeric'),header=TRUE) a<-table.element(a,as.matrix(hd[i])[1,1]) a<-table.element(a,as.matrix(attr(hd,'se')[i])[1,1]) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable.tab')

Summary of computational transaction
Raw Input	view raw input (R code)
Raw Output	view raw output of R engine
Computing time	1 seconds
R Server	Big Analytics Cloud Computing Center

Harrell-Davis Quantiles
quantiles	value	standard error
0.01	2046.24239190555	61.168504084948
0.02	2124.05986594756	55.7459736048998
0.03	2176.89075985595	48.2907270108433
0.04	2215.05415553043	40.9833981259386
0.05	2245.44228262771	43.3449665582572
0.06	2274.86681504611	51.5077635718312
0.07	2306.001751673	58.578816775524
0.08	2337.7405085378	59.846601179984
0.09	2367.48180731932	55.3092533773383
0.1	2393.4196411207	48.5864021638891
0.11	2415.5034365232	43.5559227154306
0.12	2434.93549710422	41.8294299596099
0.13	2453.1464549011	42.6857255600961
0.14	2471.14039398732	44.7556893818684
0.15	2489.43237843795	47.3427733564397
0.16	2508.30452892332	50.5533005617286
0.17	2528.03326626545	54.7362968296608
0.18	2548.92192975913	59.8714927501259
0.19	2571.17380943461	65.3319315914894
0.2	2594.7371214846	70.0900194952628
0.21	2619.23856622933	73.143526328753
0.22	2644.04649429258	73.8932294197174
0.23	2668.42712228759	72.3079871528401
0.24	2691.71747030284	68.8469720603808
0.25	2713.44699730315	64.2240303630874
0.26	2733.37989162618	59.1560836577221
0.27	2751.49252025794	54.2130648931034
0.28	2767.92199696232	49.8003400630409
0.29	2782.9164343482	46.2150145128235
0.3	2796.79706075616	43.686065289985
0.31	2809.92513293448	42.3489429826488
0.32	2822.66362874629	42.179833050642
0.33	2835.33344778208	42.964601228212
0.34	2848.17577021893	44.3563946649501
0.35	2861.3357946928	46.0012777945668
0.36	2874.87493005719	47.6590840311298
0.37	2888.80392618999	49.2533353733186
0.38	2903.1181261273	50.826777972375
0.39	2917.81555355485	52.4310025963525
0.4	2932.88945743666	54.0175672267753
0.41	2948.30267689885	55.3987771114508
0.42	2963.96255980762	56.3032714693102
0.43	2979.7160175169	56.4961908109789
0.44	2995.37476808798	55.9043537980194
0.45	3010.76644835994	54.6924614490499
0.46	3025.79523674408	53.2618179849877
0.47	3040.4908884271	52.1710055272885
0.48	3055.0285869085	51.9983906959791
0.49	3069.71128555167	53.1809717439899
0.5	3084.91733946601	55.8792276986132
0.51	3101.0258195042	59.9197951891224
0.52	3118.33803400898	64.8362053130947
0.53	3137.01575289381	69.9873171334889
0.54	3157.05405024969	74.7199220409031
0.55	3178.29901475204	78.5419084742992
0.56	3200.50785934243	81.2623490424571
0.57	3223.43349317053	83.0445693726069
0.58	3246.90299522349	84.3290480328901
0.59	3270.85705321972	85.6258666703965
0.6	3295.33021256376	87.2460991096458
0.61	3320.37736315744	89.1044901572551
0.62	3345.97928686566	90.7181773884866
0.63	3371.97420292946	91.4204569069475
0.64	3398.05283309177	90.6791245778164
0.65	3423.82402621753	88.3542913935595
0.66	3448.92223026386	84.7713437534829
0.67	3473.10755789474	80.5832482203307
0.68	3496.31591504947	76.5029757294936
0.69	3518.64584504214	73.0514167181341
0.7	3540.30165490551	70.4493420326703
0.71	3561.52911545481	68.681952020442
0.72	3582.57278925874	67.648031829967
0.73	3603.66146563524	67.2687107964565
0.74	3625.00786755128	67.4938811747492
0.75	3646.80429547481	68.2390538477464
0.76	3669.20754259923	69.3363488782298
0.77	3692.32208975242	70.5589067070703
0.78	3716.19545141383	71.7027252013536
0.79	3740.82900212047	72.6497999343106
0.8	3766.19373422585	73.3514661762611
0.81	3792.24297701978	73.7676599059618
0.82	3818.93713241114	73.8919321656155
0.83	3846.31010990331	73.9314949400382
0.84	3874.57275647254	74.4627381074256
0.85	3904.17136305041	76.2035051627034
0.86	3935.68425556424	79.3267546501435
0.87	3969.54310205555	82.9427174342329
0.88	4005.78449036473	85.5632670515846
0.89	4044.18222529498	86.5164742544186
0.9	4084.95813128252	87.3713398129386
0.91	4129.77785999533	92.0020885716157
0.92	4182.21280395745	104.005188758812
0.93	4247.01800674087	122.838102414905
0.94	4329.14987129381	144.687708199269
0.95	4434.76764591502	170.09644637103
0.96	4572.38151565164	201.400390940544
0.97	4749.76148994685	222.400096735998
0.98	4985.39116121594	241.89349587941
0.99	5314.91651830503	273.200582957074